Household CO2 Emissions: Current Status and Future Perspectives

Liu, Lina; Qu, Jianhua; Maraseni, Tek; Niu, Yibo; Zeng, Jingjing; Zhang, Lihua; Xu, Lu

doi:10.3390/ijerph17197077

Cited by 34 publications

(31 citation statements)

References 68 publications

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“…(3) The urban population linearly explains the CO 2 emission values (Equations ( 4) and ( 5)), a 1% increase of the urban population leading to a 1% increase of the CO 2 emissions. These results also confirm the findings reported by other authors [83][84][85] that the urban population scale is an important factor in residential energy consumption and CO 2 emissions. Also, as observed in Equation ( 4), the energy intensity also influences the CO 2 emissions, a 1% increase of the energy intensity leading to a 0.49% increase of the CO 2 emissions.…”

Section: Resultssupporting

confidence: 92%

National Carbon Accounting—Analyzing the Impact of Urbanization and Energy-Related Factors upon CO2 Emissions in Central–Eastern European Countries by Using Machine Learning Algorithms and Panel Data Analysis

Nuţă

Zamfir

et al. 2021

Energies

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The work at hand assesses several driving factors of carbon emissions in terms of urbanization and energy-related parameters on a panel of emerging European economies, between 1990 and 2015. The use of machine learning algorithms and panel data analysis offered the possibility to determine the importance of the input variables by applying three algorithms (Random forest, XGBoost, and AdaBoost) and then by modeling the urbanization and the impact of energy intensity on the carbon emissions. The empirical results confirm the relationship between urbanization and energy intensity on CO2 emissions. The findings emphasize that separate components of energy consumption affect carbon emissions and, therefore, a transition toward renewable sources for energy needs is desirable. The models from the current study confirm previous studies’ observations made for other countries and regions. Urbanization, as a process, has an influence on the carbon emissions more than the actual urban regions do, confirming that all the activities carried out as urbanization efforts are more harmful than the resulted urban area. It is proper to say that the urban areas tend to embrace modern, more green technologies but the road to achieve environmentally friendly urban areas is accompanied by less environmentally friendly industries (such as the cement industry) and a high consumption of nonrenewable energy.

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Section: Resultssupporting

confidence: 92%

National Carbon Accounting—Analyzing the Impact of Urbanization and Energy-Related Factors upon CO2 Emissions in Central–Eastern European Countries by Using Machine Learning Algorithms and Panel Data Analysis

Nuţă

Zamfir

et al. 2021

Energies

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“…Research on emissions in houses [34], locomotion [35,36], industry [37], avoided by electric vehicle [38], estimates at the country level [39], or policy guidelines for reducing emissions [40] were carried out. Increasingly, the existence of databases for the evaluation of air quality is being used [41].…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of Population Density on CO2 Emissions Eliminating the Influence of Climate

Zarco-Periñán

Zarco-Soto

2021

Atmosphere

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More than 50% of the world’s population lives in cities. Its buildings consume more than a third of the energy and generate 40% of the emissions. This makes cities in general and their buildings in particular priority points of attention for policymakers and utilities. This paper uses population density as a variable to know its influence on energy consumption and emissions produced in buildings. Furthermore, to show its effect more clearly, the influence of the climate was eliminated. The usual energy consumption in buildings is thermal and electrical. The study was carried out at the city level, both per inhabitant and per household. The area actually occupied by the city was considered. The proposed method was applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption per inhabitant and household in buildings. The consumption of thermal energy is elastic, while that of electrical energy is inelastic, varying more than 100% between extreme groups. Regarding CO2 emissions, the higher the population density, the higher the emissions. Emissions of electrical origin barely vary by 2% and are greater than those of thermal origin. In addition, the proportion of emissions of electrical origin, with respect to the total, decreases with increasing population density from 74% to 55%. This research aims to help policymakers and utilities to take the appropriate measures that favor the use of renewable energies and reduce CO2 emissions.

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“…In recent years, household carbon emissions have been widely discussed and have been a cause for concern [ 19 , 20 ]. The benefits of reducing household carbon emissions for the environment have been proven [ 21 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of the Cause of Household Carbon Lock-In for Chinese Urban Households

Sun

Qiao

et al. 2021

IJERPH

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Household energy conservation is an important contributor to achieve the carbon emission reduction target. However, the actual energy-saving effect of Chinese households is under expectation. One reason for this is because household energy consumption is locked in at a certain level, which has become an obstacle to household carbon emission reduction. In order to reduce this obstacle, this study explored the cause of household carbon lock-in based on grounded theory, targeting newly furnished households. A theoretical model was developed to reveal the formation mechanism of carbon lock-in effect in the purchasing process of household energy-using appliances. NVivo 12 software was used to analyze the decoration diaries of 616 sample households, and the results showed that (1) the direct antecedent of the household carbon lock-in effect was the lock-in of purchasing behavior, and the household carbon lock-in effect was mainly exhibited in the consumption path dependence (of energy-using appliances) and the solidification of energy structure; (2) the willingness to purchase household appliances was the direct antecedent of purchasing behavioral lock-in, and the cost had a moderating effect on the transformation from purchase willingness to behavioral lock-in; and (3) in the process of purchasing household appliances, reference groups, value perception, and ecological awareness can promote purchasing behavioral lock-in by affecting willingness of purchase. Suggestions to promote unlocking of household carbon were also proposed.

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Household CO2 Emissions: Current Status and Future Perspectives

Cited by 34 publications

References 68 publications

National Carbon Accounting—Analyzing the Impact of Urbanization and Energy-Related Factors upon CO2 Emissions in Central–Eastern European Countries by Using Machine Learning Algorithms and Panel Data Analysis

National Carbon Accounting—Analyzing the Impact of Urbanization and Energy-Related Factors upon CO2 Emissions in Central–Eastern European Countries by Using Machine Learning Algorithms and Panel Data Analysis

Influence of Population Density on CO2 Emissions Eliminating the Influence of Climate

Analysis of the Cause of Household Carbon Lock-In for Chinese Urban Households

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